• Smart Structures and Systems
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• v.20 no.1
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• pp.61-74
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• 2017

One of the most reliable and simplest tools for structural vibration control in civil engineering is Tuned Mass Damper, TMD. Provided that the frequency and damping parameters of these dampers are tuned appropriately, they can reduce the vibrations of the structure through their generated inertia forces, as they vibrate continuously. To achieve the optimal parameters of TMD, many different methods have been provided so far. In old approaches, some formulas have been offered based on simplifying models and their applied loadings while novel procedures need to model structures completely in order to obtain TMD parameters. In this paper, with regard to the nonlinear decision-making of fuzzy systems and their enough ability to cope with different unreliability, a method is proposed. Furthermore, by taking advantage of both old and new methods a fuzzy system is designed to be operational and reduce uncertainties related to models and applied loads. To design fuzzy system, it is required to gain data on structures and optimum parameters of TMDs corresponding to these structures. This information is obtained through modeling MDOF systems with various numbers of stories subjected to far and near field earthquakes. The design of the fuzzy systems is performed by three methods: look-up table, the data space grid-partitioning, and clustering. After that, rule weights of Mamdani fuzzy system using the look-up table are optimized through genetic algorithm and rule weights of Sugeno fuzzy system designed based on grid-partitioning methods and clustering data are optimized through ANFIS (Adaptive Neuro-Fuzzy Inference System). By comparing these methods, it is observed that the fuzzy system technique based on data clustering has an efficient function to predict the optimal parameters of TMDs. In this method, average of errors in estimating frequency and damping ratio is close to zero. Also, standard deviation of frequency errors and damping ratio errors decrease by 78% and 4.1% respectively in comparison with the look-up table method. While, this reductions compared to the grid partitioning method are 2.2% and 1.8% respectively. In this research, TMD parameters are estimated for a 15-degree of freedom structure based on designed fuzzy system and are compared to parameters obtained from the genetic algorithm and empirical relations. The progress up to 1.9% and 2% under far-field earthquakes and 0.4% and 2.2% under near-field earthquakes is obtained in decreasing respectively roof maximum displacement and its RMS ratio through fuzzy system method compared to those obtained by empirical relations.

• Korean Journal of Adult Nursing
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• v.12 no.1
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• pp.52-63
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• 2000

In Korea, most of the patients with chronic liver diseases have been using some kind of alternative therapies at home. however, the question is why do people turn to alternative therapy and how the patients are able to use the alternative therapies widely, though the effects have not been proven scientifically. Therefore, it is necessary to explore the process of the patients' experiences using the alternative therapies. The 16 participants were from internalmedical departments in hospital and the permission was received to participate in this study from the subjects. The data were collected with interviews and participants observations, analyzed by the grounded theory methodology of Strauss and Corbin(1990). With the analysis of the data, 15 categories were generated such as psychological pressures, barriers of role performances, distrusts of western medicine, blind obediences to the treatments, attitudes towards alternative therapies, supportive systems, obstacles to taking alternative therapies, financial burdens, collecting informations, pursuing alternative modalities, efforting diversities, analyzing by themselves, managing the body, accepting the disease, and ambivalence. The paradigm model was developed to identify the relationships of categories. The central phenomenon of the experiences of seeking alternative therapies was named jagi momdasrim. The central concept of jagi momdasrim is a mind-set to desire to wellness and to take more responsibility for one's own healing by pursuing alternate healing modalities rather than the western medical system. The process of jagi momdasrim evolved several stages such as seeking, finding, struggling, overcoming, fulfilling, and governing the diseases. Four patterns of taking alternative therapies were found as follows: the bulsin-chujong-hyung, the suyoung-hyung, the yangdari-gulchiki-hyung, the chamjae-hyung. In conclusion, the phenomenon of alternative therapies as consumer-driven force to heal the chronic liver diseases of the patients could be explained as an adaptive behavior through the process of jagi momdasrim. However, since most of the participants practicing some kind of alternative therapies had no evidences of its effects and never tried to consult with their medical doctors about alternative therapies, we should approach more actively. Therefore, it is recommended for nurses to listen and watch the patients behaviors of using alternative therapies and find out how to educate the patients about the proper and safe way to take the alternative therapies.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.139-146
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• 2002

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement learning is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to choose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement learning is different from supervised learning in the sense that there is no presentation of input-output pairs as training examples. Furthermore, model-free reinforcement learning algorithms like Q-learning do not require defining or learning any models of the surrounding environment. Nevertheless these algorithms can learn the optimal policy if the agent can visit every state-action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem, we suggest Adaptive Mediation-based Modular Q-Learning (AMMQL) as an improvement of the existing Modular Q-Learning (MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state space effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. In this paper we use the AMMQL algorithn as a learning method for dynamic positioning of the robot soccer agent, and implement a robot soccer agent system called Cogitoniks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.1C
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• pp.26-35
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• 2006

In this paper, an automatic mobile robot system for a intelligent path planning using the detection scheme of the spatial coordinates based on stereo camera is proposed. In the proposed system, face area of a moving person is detected from a left image among the stereo image pairs by using the YCbCr color model and its center coordinates are computed by using the centroid method and then using these data, the stereo camera embedded on the mobile robot can be controlled for tracking the moving target in real-time. Moreover, using the disparity map obtained from the left and right images captured by the tracking-controlled stereo camera system and the perspective transformation between a 3-D scene and an image plane, depth information can be detected. Finally, based-on the analysis of these calculated coordinates, a mobile robot system is derived as a intelligent path planning and a estimation. From some experiments on robot driving with 240 frames of the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the mobile robot and the objects, and relative distance between the other objects is found to be very low value of $2.19\%$ and $1.52\%$ on average, respectably.

• Journal of KIISE:Information Networking
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• v.34 no.6
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• pp.493-504
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• 2007

With the advance and proliferation of computer and wireless network technology, it is common to access to network through the wireless network using mobile device. The ratio of using the streaming media out of many applications through the network is increasing not only in the wired network but also in the wireless network. The streaming media is much bigger than other contents and requires more network bandwidth to communicate and more computing resources to process. However the mobile devices have relatively poor computing resource and low network bandwidth. If the streaming media service is provided for mobile devices without any consideration about the network bandwidth and computing power, it is difficult for the client to get the service of high quality. Since especially mobile devices are supported with very limited energy capacity from the battery, the streaming media service should be adjusted to the varying energy state of mobile devices to ensure the complete playback of streaming media. In this paper, we propose a new method to guarantee the complete playback time of the streaming media for the mobile clients by dynamically controlling transmitted frame rate to the client according to the estimated available time of mobile device using battery model reflecting the characteristic of the battery. Since the proposed method controls the number of frames transmitting to the client according to the energy state of the mobile device, the complete playback time is guaranteed to mobile clients.

• Resources Recycling
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• v.27 no.1
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• pp.84-91
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• 2018

In this study, a novel soft information based most probable classification scheme is proposed for sorting recyclable metal alloys with laser induced breakdown spectroscopy (LIBS). Regression analysis with LIBS captured spectrums for estimating concentrations of common elements can be efficient for classifying unknown arbitrary metal alloys, even when that particular alloy is not included for training. Therefore, partial least square regression (PLSR) is employed in the proposed scheme, where spectrums of the certified reference materials (CRMs) are used for training. With the PLSR model, the concentrations of the test spectrum are estimated independently and are compared to those of CRMs for finding out the most probable class. Then, joint soft information can be obtained by assuming multi-variate normal (MVN) distribution, which enables to account the probability measure or a prior information and improves classification performance. For evaluating the proposed schemes, MVN soft information is evaluated based on PLSR of LIBS captured spectrums of 9 metal CRMs, and tested for classifying unknown metal alloys. Furthermore, the likelihood is evaluated with the radar chart to effectively visualize and search the most probable class among the candidates. By the leave-one-out cross validation tests, the proposed scheme is not only showing improved classification accuracies but also helpful for adaptive post-processing to correct the mis-classifications.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.1
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• pp.9-26
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• 2005

In the pursuit of ever higher levels of performance, recent computer systems have made use of deep pipeline, dynamic scheduling and multi-issue superscalar processor technologies. In this situations, branch prediction schemes are an essential part of modem microarchitectures because the penalty for a branch misprediction increases as pipelines deepen and the number of instructions issued per cycle increases. In this paper, we propose a novel branch prediction scheme, direction-gshare(d-gshare), to improve the prediction accuracy. At first, we model a neural network with the components that possibly affect the branch prediction accuracy, and analyze the variation of their weights based on the neural network information. Then, we newly add the component that has a high weight value to an original gshare scheme. We simulate our branch prediction scheme using Simple Scalar, a powerful event-driven simulator, and analyze the simulation results. Our results show that, compared to bimodal, two-level adaptive and gshare predictor, direction-gshare predictor(d-gshare. 3) outperforms, without additional hardware costs, by up to 4.1% and 1.5% in average for the default mont of embedded direction, and 11.8% in maximum and 3.7% in average for the optimal one.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.12
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• pp.109-120
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• 1998

An image segmentation approach based on the fuzzy worm searching and MIN-MAX clustering algorithm is proposed in this paper. This algorithm deals with fuzzy worm value and min-max node at a gross scene level, which investigates the edge information including fuzzy worm action and spatial relationship of the pixels as the parameters of its objective function. But the conventional segmentation methods for edge extraction generally need the mask information for the algebraic model, and take long run times at mask operation, whereas the proposed algorithm has single operation according to active searching of fuzzy worms. In addition, we also propose both genetic fuzzy worm searching and genetic min-max clustering using genetic algorithm to complete clustering and fuzzy searching on grey-histogram of image for the optimum solution, which can automatically determine the size of ranges and has both strong robust and speedy calculation. The simulation results showed that the proposed algorithm adaptively divided the quantized images in histogram region and performed single searching methods, significantly alleviating the increase of the computational load and the memory requirements.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.8 s.111
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• pp.773-787
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• 2006

An airborne radar is an essential aviation electronic system for the aircraft to perform various civil and/or military missions in all weather environments. This paper presents the design, development, and test results of the multi-mode X-band pulsed Doppler radar system test model for helicopter-borne flight test. This radar system consists of 4 LRUs(Line-Replacement Unit), which include antenna unit, transmitter and receiver unit, radar signal & data processing unit and display Unit. The developed core technologies include the planar array antenna, TWTA transmitter, coherent I/Q detector, digital pulse compression, MTI, DSP based Doppler FFT filter, adaptive CFAR, moving clutter compensation, platform motion stabilizer, and tracking capability. The design performance of the developed radar system is verified through various ground fixed and moving vehicle test as well as helicopter-borne field tests including MTD(Moving Target Detector) capability for the Doppler compensation due to the moving platform motion.

• The Journal of Internal Korean Medicine
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• v.29 no.1
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• pp.117-129
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• 2008

Background & Objective : Naeso-san(NSS) has been used for the treatment of functional dyspepsia, regarded as a gastric dysmotility disease. A main cause of gastric dysmotility is antral dilatation or antroduodenal uncoordination. Therefore, we investigated the effect of NSS on gastric motility and its mechanism of action, as well as the morphologic changes in antral dilatated rats. Methods : Antral dilatated rats were induced by wrapping a nonabsorbable rubber ring(D:6mm, W:4mm, T:1mm) around the 1st portion of the duodenum for 8 weeks. Then morphologic changes were investigated and compared with normal intact rats before and after 8 weeks. Gastric emptying was measured by administration of normal saline(NS) or NSS in normal intact and antral dilatated rats. In another series of experiments to evaluate the mechanism of NSS under delayed conditions, normal intact rats were treated with atropine sulfate(1mg/kg, s.c.), quinpirole HCl(0.3mg/kg, i.p.), $NAME(N^{G}-nitro-L-arginine$ methyl ester, 75mg/kg, s.c.) and cisplatin(10mg/kg, i.p.), respectively. The myoelectrical activity of the gastric smooth muscle was recorded in normal intact and antral dilatated rats. The contractile waves were measured for 30 minutes before and after administration of each solution(NS, NSS). Results : Body weight gain of antral dilatated rats was significantly lower than that of the controls. Futhermore, we found the thickness of the mucosal and muscular layers and surface area of the stomach increased significantly compared with controls. NSS 278㎎/㎏ improved gastric emptying more than normal saline or NSS 93mg/kg in normal intact(p=0.026) and antral dilatated rats(p=0.03). NSS enhanced gastric emptying significantly in the NAME treated group(p=0.002). NSS 278mg/kg increased the significant postprandial dominant power than that of NS in normal intact rats, whereas there was no statistical significance in antral dilatated rats. Conclusions : NSS stimulates gastric motility through the cholinergic pathway. We expect that pathologic model with antral dilatation can be used as an exprimental tool which is similar to dyspepsia and NSS would be effective especially in dysmotility-like functional dyspepsia with antral dilatation or impaired reservoir functions such as gastric adaptive relaxation.